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http://elartu.tntu.edu.ua/handle/lib/51449| Títol: | Parallel Processing for Real – Time Stream Analytics |
| Autor: | Mac-Gatus, Emmanuel Yaw |
| Affiliation: | ТНТУ ім. І. Пулюя, Факультет комп’ютерно-інформаційних систем і програмної інженерії, Кафедра комп’ютерних наук, м. Тернопіль, Україна |
| Bibliographic description (Ukraine): | Mac-Gatus E. Y. Parallel Processing for Real – Time Stream Analytics : Bachelor’s qualification thesis in specialty 122 Computer Science / supervisor R. Zolotyi. — Ternopil : Ternopil Ivan Puluj National Technical University, 2026. — 81 p. |
| Bibliographic reference (2015): | Mac-Gatus E. Y. Parallel Processing for Real – Time Stream Analytics: Bachelor’s qualification thesis in specialty 122 Computer Science / supervisor R. Zolotyi. Ternopil: Ternopil Ivan Puluj National Technical University, 2026. 81 p. |
| Data de publicació: | 26-de -2026 |
| Submitted date: | 12-de -2026 |
| Date of entry: | 28-de -2026 |
| Editorial: | ТНТУ ім. І.Пулюя, ФІС, м. Тернопіль, Україна |
| Country (code): | UA |
| Place of the edition/event: | Тернопіль |
| Supervisor: | Золотий, Роман Захарійович Zolotyi, Roman |
| Committee members: | Голотенко, Олександр Сергійович Holotenko, Oleksandr |
| UDC: | 004.415.5:004.62 |
| Paraules clau: | 122 комп'ютерні науки аналітика бакалаврська робота великі дані паралельна обробка реальний час потоки даних apache flink apache kafka big data parallel computing real-time analytics stream processing |
| Page range: | 81 |
| Resum: | The qualification work is devoted to the research and implementation of parallel data processing methods for real-time analytics systems. The first chapter examines the theoretical foundations of Stream Processing and provides a comparative analysis of modern frameworks such as Apache Kafka, Flink, and Spark Streaming. The second chapter focuses on designing a system architecture that utilizes parallelism principles to ensure low latency and high throughput when processing large volumes of information. The third chapter presents the practical implementation of a system prototype, conducts experimental studies on scalability, and evaluates the impact of the number of parallel nodes on query processing speed. The work demonstrates the advantages of distributed computing for instant event analysis tasks. Separate sub-sections include an analysis of labor safety and an economic evaluation of the development |
| Descripció: | Роботу виконано на кафедрі комп'ютерних наук Тернопільського національного технічного університету імені Івана Пулюя. Захист відбудеться 26.01.2026р. на засіданні екзаменаційної комісії №32 у Тернопільському національному технічному університеті імені Івана Пулюя |
| Content: | INTRODUCTION 1 THEORETICAL ANALYSIS OF STREAM PROCESSING TECHNOLOGIES 1.1 Concepts of real-time data processing 1.2 Review of distributed computing frameworks 1.3 Challenges in processing high-velocity data streams 2 ARCHITECTURE AND DESIGN OF PARALLEL PROCESSING SYSTEM 2.1 System requirements and functional components 2.2 Modeling parallel data flows and synchronization 2.3 Selection of tools for stream analytics implementation 3 IMPLEMENTATION AND PERFORMANCE EVALUATION 3.1 Development of the parallel processing prototype 3.2 Testing scalability and latency benchmarks 3.3 Analysis of experimental results 4 ECONOMIC JUSTIFICATION OF THE PROPOSED SYSTEM 5 OCCUPATIONAL HEALTH AND SAFETY IN EMERGENCY SITUATIONS CONCLUSIONS REFERENCES |
| URI: | http://elartu.tntu.edu.ua/handle/lib/51449 |
| Copyright owner: | © Mac-Gatus Emmanuel Yaw, 2026 |
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| Content type: | Bachelor Thesis |
| Apareix a les col·leccions: | 122 — Компʼютерні науки (бакалаври) |
Arxius per aquest ítem:
| Arxiu | Descripció | Mida | Format | |
|---|---|---|---|---|
| KRB_2026_ISN-43_Mac-Gatus_EY.pdf | Дипломна робота | 3,27 MB | Adobe PDF | Veure/Obrir |
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